Startup Jobs Scraper

Extract startup and remote job listings from Startup.jobs in a fast, reliable, automated workflow. Collect complete hiring data including job titles, company details, salary ranges, posting dates, and descriptions for research, monitoring, and analysis. This scraper is built for teams that need consistent job market data at scale.

Features

• Comprehensive Job Collection — Gather job records with title, company, location, salary, tags, and posting metadata.
• Description Enrichment — Capture detailed job descriptions and clean text for analysis-ready datasets.
• Flexible Search Inputs — Filter by keyword, location, and listing URL to target specific job segments.
• Scalable Output Control — Set result and page limits to balance data depth, speed, and cost.
• Reliable Anti-Blocking Handling — Keep extraction stable even when websites apply protection layers.

Use Cases

Talent Intelligence

Track hiring demand across startup roles, locations, and experience levels. Build weekly or daily trend snapshots for leadership and recruiting teams.

Recruitment Operations

Create fresh candidate sourcing datasets by collecting new openings and role attributes automatically. Reduce manual job-board monitoring effort.

Compensation Research

Analyze salary ranges by function, seniority, and market. Support compensation benchmarking and talent planning with structured data.

Product and Market Research

Monitor role requirements, skills demand, and company hiring patterns over time. Identify emerging trends in startup hiring strategies.

Job Alert Platforms

Feed downstream tools and internal dashboards with normalized job records. Power notifications, matching logic, and searchable job databases.

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Input Parameters

Parameter	Type	Required	Default	Description
startUrl	String	No	—	Custom Startup.jobs listing URL. When provided, it overrides other search filters.
keyword	String	No	""	Search phrase for job targeting, such as role, function, or skill keywords.
location	String	No	"Remote"	Location filter. Use "Remote" for remote-first job collection.
collectDetails	Boolean	No	true	Include enriched job descriptions and additional detail fields.
results_wanted	Integer	No	20	Maximum number of jobs to collect in a run (1 to 500).
max_pages	Integer	No	3	Maximum number of listing pages to process (1 to 20).
maxConcurrency	Integer	No	2	Concurrency setting for extraction stability and speed (1 to 5).

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Output Data

Each dataset item contains:

Field	Type	Description
id	String	Unique job identifier.
title	String	Job title.
company	String	Hiring company name.
location	String	Job location or remote status.
job_type	String	Employment type (for example full-time or part-time).
salary	String	Human-readable salary value when available.
posted_at	String	Job publish timestamp.
description_text	String	Plain text job description for analysis workflows.
description_html	String	Rich job description content.
company_logo	String	Company logo URL when available.
apply_link	String	Application or job destination link.
url	String	Job page URL.
source	String	Extraction source indicator.
fetched_at	String	Data collection timestamp (ISO format).
tags	Array	Role or topic tags related to the job.
workplace_type	String	Workplace model label.
employment_type	String	Employment type code from listing data.
experience_bucket	String	Experience level category when provided.
salary_min	Number	Minimum salary value when available.
salary_max	Number	Maximum salary value when available.
salary_currency	String	Salary currency code.
city	String	City value when available.
country	String	Country value when available.
company_slug	String	Company slug identifier.

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Usage Examples

Basic Remote Collection

{
  "location": "Remote",
  "results_wanted": 20
}

Keyword-Focused Extraction

{
  "keyword": "software engineer",
  "location": "Remote",
  "results_wanted": 50,
  "max_pages": 5,
  "collectDetails": true
}

Custom Listing URL

{
  "startUrl": "https://startup.jobs/remote-jobs?w=remote&q=data+scientist",
  "results_wanted": 30,
  "max_pages": 3,
  "collectDetails": true
}

Sample Output

{
  "id": "6654883",
  "title": "Senior Full Stack Engineer",
  "company": "Solace",
  "location": "Remote",
  "job_type": "Full Time",
  "salary": "USD 150000 - 200000",
  "posted_at": "2026-01-22T16:50:47Z",
  "description_text": "As a Full Stack Engineer, you'll join a talented team and own delivery from requirements through release...",
  "description_html": "<div class=\"trix-content\">...</div>",
  "company_logo": "https://startup.jobs/logos/34127",
  "apply_link": "https://startup.jobs/apply/4cec53b4-9d8e-4ce7-989b-b9f0e163de13",
  "url": "https://startup.jobs/senior-full-stack-engineer-solace-6654883",
  "source": "listing+details",
  "fetched_at": "2026-02-14T05:28:50.151Z",
  "tags": ["Engineer", "Full Stack", "Senior"]
}

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Tips for Best Results

Start with QA-Friendly Limits

• Begin with results_wanted: 20 to validate settings quickly.
• Increase volume after confirming output quality and stability.

Use Specific Keywords

• Combine role and specialty terms to narrow results.
• Use broader keywords when building market-wide datasets.

Tune Concurrency Carefully

• Keep maxConcurrency low for stability on protected pages.
• Increase gradually when throughput is stable.

Keep Runs Fast

• Start with results_wanted: 20 and scale up once the run profile is stable.
• Increase maxConcurrency gradually and monitor runtime versus failure rate.

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Integrations

Connect your dataset with:

• Google Sheets — Share and analyze hiring data quickly.
• Airtable — Build searchable internal hiring intelligence tables.
• Make — Automate downstream workflows and alerts.
• Zapier — Trigger notifications and CRM updates.
• Webhooks — Deliver fresh run results to your own endpoints.

Export Formats

• JSON — API and engineering workflows.
• CSV — Spreadsheet analysis and BI import.
• Excel — Business reporting and operations review.
• XML — Legacy system integrations.

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Frequently Asked Questions

How many jobs can I collect per run?

You can request up to 500 items per run using results_wanted.

Can I collect full job descriptions?

Yes. Keep collectDetails enabled to gather enriched description fields.

Why are some fields empty?

Some listings do not publish every field (for example salary or location detail), so those values may be null.

How do I make runs more reliable?

Use residential proxies, keep concurrency moderate, and start with focused filters.

Can I schedule this scraper daily?

Yes. You can schedule runs from Apify to keep your dataset continuously updated.

Is this suitable for analytics pipelines?

Yes. The output is normalized and export-friendly for dashboards, alerts, and data warehouses.

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Support

For issues or feature requests, use support channels in the Apify Console.

Resources

• Apify Documentation
• Apify API Reference
• Apify Scheduling

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Legal Notice

This actor is intended for legitimate data collection and analysis. Users are responsible for complying with applicable laws, platform terms, and responsible data usage practices.